In mobile ad-hoc cognitive radio networks (CRMANET), accurately identifying primary user spectrum occupancy is an important requirement in successful utilization of the spectrum by the secondary user. This is made difficult by malicious mobile secondary users launching spectrum sensing data falsification (SSDF) attacks, byzantine failures of devices, primary user signal fading, and hidden terminal problems. Another ability of these malicious users is to use their mobility to hide under the changing neighborhood. Existing state of the art techniques either consider a centralized approach in decision making or when considering an ad-hoc network, do not take into account the mobility of the devices which adds unique limitations. We present a light weight multi-fusion based distributed spectrum sensing scheme (MFDSS) in a mobile ad-hoc secondary user network to overcome the aforementioned problems. MFDSS allows each secondary user to collect semi-global information to make decisions in a distributed manner. It uses outlier detection and data fusion to remove incorrect sensing data generated by byzantine failures. Reputation information of the devices is used to suppress a SSDF attack. MFDSS incorporates a reputation propagation and fusion scheme to prevent malicious devices from hiding behind changing topology and to maintain the freshness of the reputation information. Additionally, MFDSS includes an incubation period to discourage devices from changing identity to perform a Sybil attack or to mask a bad reputation. Detailed analysis is presented and the results show significant improvement in correct primary user spectrum occupancy identification. We also show that without the reputation propagation of MFDSS, a malicious device is able to move its position and hide its malicious intentions in the new neighborhood.

In cognitive radio networks, secondary users need to accurately identify primary user spectrum occupancy in order to use it. Accurate spectrum sensing is hindered by signal fading, hidden terminal problems, byzantine failures, etc. Centralized cooperative spectrum sensing works well if the secondary user network is infrastructure based and there is a centralized basestation making network wide decisions. When the secondary users network is a cognitive radio mobile ad-hoc network (CR-MANET), then decisions need to be made in a distributed manner and cooperative spectrum sensing introduces additional problems due to the presence of malicious users. These malicious secondary users encourage other secondary users to make a wrong spectrum occupancy decision by feeding inaccurate measurements. We study this problem and present a solution to improve primary user spectrum occupancy identification accuracy in the presence of malicious users. A virtual neighbor cluster is created in which the mobile device forms an evolving cluster of past neighbor devices that aids in validating the input gathered from the current neighboring devices. Next, a recursive partitioning around medoids based clustering is performed to identify a tightly bound set of valid inputs. The validated inputs from both the methods form a decision cluster and the data is fused to get the decision on primary user occupancy. Two data fusion strategies are presented and their use depends on the amount of dynamism in the CR-MANET. The analysis and results show the accuracy of primary user occupancy detection even in the presence of large number of malicious users and signal measurement errors.

Many efforts have been devoted to maximizing network throughput in a multichannel multiradio wireless mesh network. Most current solutions are based on either purely static or purely dynamic channel allocation approaches. In this paper, we propose a hybrid multichannel multiradio wireless mesh networking architecture, where each mesh node has both static and dynamic interfaces. We first present an Adaptive Dynamic Channel Allocation protocol (ADCA), which considers optimization for both throughput and delay in the channel assignment. In addition, we also propose an Interference and Congestion Aware Routing protocol (ICAR) in the hybrid network with both static and dynamic links, which balances the channel usage in the network. Our simulation results show that compared to previous works, ADCA reduces the packet delay considerably without degrading the network throughput. The hybrid architecture shows much better adaptivity to changing traffic than purely static architecture without dramatic increase in overhead, and achieves lower delay than existing approaches for hybrid networks.

Securing a sensor network poses a variety of problems. Of those, an important one is of providing privacy to the event-detecting sensor node and integrity to the data gathered by the node. Compromised source privacy can inadvertently leak event location. Safeguarding the privacy of the source node is important, as sensor networks hold critical roles in military application, tracking endangered species, etc. Existing techniques in sensor networks use either random walk path or generate fake event packets to make it hard for an adversary to trace back to the source, since encryption alone may not help prevent a traffic analysis attack. In this work, without using traditional overhead-intensive methods, we present a scheme for hiding source information using cryptographic techniques incurring lower overhead. The packet is modified en route by dynamically selected nodes to make it difficult for a malicious entity to trace back the packet to a source node and also to prevent packet spoofing. This is important because the adversary model considers a super-local eavesdropper having the ability to compromise sensor nodes. Additionally, we provide a method for the base station to recover corrupted packets and identify the location of the compromised node. We analyze the ability of our proposed scheme to withstand different attacks and demonstrate its efficiency in terms of overhead and functionality when compared to existing work.

With respect to ground level, wireless communication signal strength increases with the elevation of communicating wireless sensor network devices, within practical bounds. Jumping sensors are mobile sensors that provide relocation capabilities and a temporary increase in elevation can be utilized for improving communication. This paper provides a comprehensive multidimensional analysis for jumping sensors. It studies the main factors that impact the Received Signal Strength (RSS) in sensor communication, and performs a comparative analysis between theoretical and experimental results. Sensor elevation from ground level is a key factor, which is often neglected, and plays an important role for successful wireless communication. The impact of jump height manipulation on a jumping sensor to the packet transmission goodput is presented. An airborne two-way communication scheme is defined and studied with experiments. The results indicate the effectiveness of utilizing the change in elevation of a jumping sensor to increase communication range. Since energy is at premium in sensor nodes, the operational energy cost of a jumping sensor prototype is studied in detail. A jumping sensor network is simulated with the parameters learned from the experimental results and the jumping sensor prototype analysis. Simulation results show the enhancement in connectivity and the feasibility of a jumping sensor network.

In a sensor network, an important problem is to provide privacy to the event detecting sensor node and integrity to the data gathered by the node. Compromised source privacy can inadvertently leak event location. Existing techniques use either random walk path or generate fake event packets to make it hard for the adversary to traceback to the source, since encryption alone may not help prevent a traffic analysis attack. In this work, without using the traditional overhead intensive methods, we present a scheme to hide source information using cryptographic techniques incurring lower overhead. The packet is modified en route by dynamically selected nodes to make it difficult for a malicious entity to traceback the packet to a source node and also prevent packet spoofing. This is important because the adversary model considers a super-local eavesdropper having the ability to compromise sensor nodes. We analyze the ability of our proposed scheme to withstand different attacks and demonstrate its efficiency in terms of overhead and functionality when compared to existing work.

In wireless sensor networks, communication signal strength weakens as the distance between sensors increases, which increases the tendency for transmitted packets to be lost. This paper provides a novel method of incorporating the hopping capability of a sensor to increase its communication range, which results in increased connectivity and sensed coverage area. Furthermore, jump heights can be manipulated to enhance packet transmissions. Since energy is at premium within sensor nodes, we present a Hopping Sensor Network Model (HSNM) and an energy conserving Hopping Sensor Routing Protocol (HSRP), which aims to optimize communication paths while balancing energy depletion in the network. Results from practical in-field experiments and simulations demonstrate the effectiveness of the approach when employed over a wireless hopping sensor network by showing increased network connectivity and the total area covered. HSRP simulations demonstrated 20% energy saving while increasing the packet delivery. The HSRP results in far less number of dead nodes, especially the high traffic nodes that are closer to the base station.

Many efforts have been devoted to maximizing network throughput in a multi-channel multi-radio wireless mesh network. Current solutions are based on either pure static or pure dynamic channel allocation approaches. In this paper, we propose a hybrid multi-channel multi-radio wireless mesh networking architecture, where each mesh node has both static and dynamic interfaces. We first present an Adaptive Dynamic Channel Allocation protocol (ADCA), which considers optimization for both throughput and delay in the channel assignment. In addition, we also propose an Interference and Congestion Aware Routing protocol (ICAR) in the hybrid network with both static and dynamic links, which balances the channel usage in the network. Compared to previous work, our simulation results show that ADCA reduces the packet delay considerably without degrading the network throughput. Moreover, the hybrid architecture shows much better adaptivity to changing traffic than pure static architecture without dramatic increase in overhead.

Compromised sensor nodes may collude to segregate a specific region of the sensor network preventing event reporting packets in this region from reaching the basestation. Additionally, they can cause skepticism over all data collected. Identifying and segregating such compromised nodes while identifying the type of attack with a certain confidence is critical to the smooth functioning of a sensor network. Existing work specializes in preventing or identifying specific type of attack and lacks a unified architecture to identify multiple attack types. Camouflage Event Based Malicious Node Detection Architecture (CENDA) is a proactive architecture that uses camouflage events generated by mobile-nodes to detect malicious nodes while identifying the type of attack. We exploit the spatial and temporal information of camouflage event while analyzing the packets to identify malicious activity. We simulated CENDA to compare its performance with other techniques that provide protection against individual attack types and the results show marked improvement in malicious node detection while having significantly less false positives. Moreover, CENDA is able to identify the type of malicious activity and is flexible to be configured to include other attack types in future.

Security is one of the top concerns when sensors are deployed in hostile environments for military applications. Attacks on sensor nodes can be categorized into two types: attacks through radio signals to alter the functionalities of sensors and physical attacks; which may completely damage sensors. We show that the former is easier to launch and more disguised, thus more hazardous. The layered framework proposed in this paper is specially designed to defend against the first type of attacks. Different from precious reputation-based approaches or data mining technologies which usually incur large communication and computation overhead, our solution only involves localized computation which is less intensive, thus can be implemented on-board with little burden on current MICA2 platforms. Besides identifying malicious nodes, our solution can also recover the normal functionalities of sensors, which have been altered by malicious radio signals